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Volumn , Issue , 2009, Pages 1542-1551

Polynomial to linear: Efficient classification with conjunctive features

Author keywords

[No Author keywords available]

Indexed keywords

DEPENDENCY PARSING; FEATURE VECTORS; GIVEN FEATURES; PRECOMPUTE;

EID: 80053398078     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (15)

References (40)
  • 1
    • 34547984768 scopus 로고    scopus 로고
    • 1-regularized log-linear models
    • Galen Andrew and Jianfeng Gao. 2007. Scalable training of L1-regularized log-linear models. In Proc. ICML 2007, pages 33-40.
    • (2007) Proc. ICML 2007 , pp. 33-40
    • Andrew, G.1    Gao, J.2
  • 2
    • 0024735522 scopus 로고
    • An efficient digital search algorithm by using a double-array structure
    • September
    • Jun'ichi Aoe. 1989. An efficient digital search algorithm by using a double-array structure. IEEE Transactions on Software Engineering, 15(9):1066-1077, September.
    • (1989) IEEE Transactions on Software Engineering , vol.15 , Issue.9 , pp. 1066-1077
    • Jun'ichi, A.1
  • 3
    • 0002652285 scopus 로고    scopus 로고
    • A maximum entropy approach to natural language processing
    • March
    • Adam Berger, Stephen Della Pietra, and Vincent Della Pietra. 1996. A maximum entropy approach to natural language processing. Computational Linguistics, 22(1):39-71, March.
    • (1996) Computational Linguistics , vol.22 , Issue.1 , pp. 39-71
    • Berger, A.1    Pietra, S.D.2    Pietra, V.D.3
  • 4
    • 46749083938 scopus 로고    scopus 로고
    • Power-law relationship and self-similarity in the itemset support distribution: Analysis and applications
    • August
    • Kun-Ta Chuang, Jiun-Long Huang, and Ming-Syan Chen. 2008. Power-law relationship and self-similarity in the itemset support distribution: analysis and applications. The VLDB Journal, 17(5):1121-1141, August.
    • (2008) The VLDB Journal , vol.17 , Issue.5 , pp. 1121-1141
    • Chuang, K.-T.1    Huang, J.-L.2    Chen, M.-S.3
  • 5
    • 34249753618 scopus 로고
    • Supportvector networks
    • September
    • Corinna Cortes and Vladimir Vapnik. 1995. Supportvector networks. Machine Learning, 20(3):273-297, September.
    • (1995) Machine Learning , vol.20 , Issue.3 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 6
    • 84864067385 scopus 로고    scopus 로고
    • Support vector machines on a budget
    • Bernhard Schölkopf, John Platt, and Thomas Hofmann, editors. The MIT Press
    • Ofer Dekel and Yoram Singer. 2007. Support vector machines on a budget. In Bernhard Schölkopf, John Platt, and Thomas Hofmann, editors, Advances in Neural Information Processing Systems 19, pages 345-352. The MIT Press.
    • (2007) Advances in Neural Information Processing Systems , vol.19 , pp. 345-352
    • Dekel, O.1    Singer, Y.2
  • 7
    • 55249109544 scopus 로고    scopus 로고
    • The forgetron: A kernel-based perceptron on a budget
    • January
    • Ofer Dekel, Shai Shalev-Shwartz, and Yoram Singer. 2008. The forgetron: A kernel-based perceptron on a budget. SIAM Journal on Computing, 37(5):1342-1372, January.
    • (2008) SIAM Journal on Computing , vol.37 , Issue.5 , pp. 1342-1372
    • Dekel, O.1    Shalev-Shwartz, S.2    Singer, Y.3
  • 8
    • 33746086325 scopus 로고    scopus 로고
    • Engineering the LOUDS succinct tree representation
    • O'Neil Delpratt, Naila Rahman, and Rajeev Raman. 2006. Engineering the LOUDS succinct tree representation. In Proc. WEA 2006, pages 134-145.
    • (2006) Proc. WEA 2006 , pp. 134-145
    • O'neil, D.1    Rahman, N.2    Raman, R.3
  • 9
    • 0038217041 scopus 로고    scopus 로고
    • The distribution of n-grams
    • February.
    • Leo Egghe. 2000. The distribution of n-grams. Scientometrics, 47(2):237-252, February.
    • (2000) Scientometrics , vol.47 , Issue.2 , pp. 237-252
    • Egghe, L.1
  • 11
    • 84860542469 scopus 로고    scopus 로고
    • A comparative study of parameter estimation methods for statistical natural language processing
    • Jianfeng Gao, Galen Andrew, Mark Johnson, and Kristina Toutanova. 2007. A comparative study of parameter estimation methods for statistical natural language processing. In Proc. ACL 2007, pages 824-831.
    • (2007) Proc. ACL 2007 , pp. 824-831
    • Gao, J.1    Andrew, G.2    Johnson, M.3    Toutanova, K.4
  • 12
    • 80053433160 scopus 로고    scopus 로고
    • SplitSVM: Fast, space-efficient, non-heuristic, polynomial kernel computation for NLP applications
    • Short Papers
    • Yoav Goldberg and Michael Elhadad. 2008. splitSVM: Fast, space-efficient, non-heuristic, polynomial kernel computation for NLP applications. In Proc. ACL 2008, Short Papers, pages 237-240.
    • (2008) Proc. ACL 2008 , pp. 237-240
    • Goldberg, Y.1    Elhadad, M.2
  • 13
    • 85117711027 scopus 로고    scopus 로고
    • Exponential priors for maximum entropy models
    • Joshua Goodman. 2004. Exponential priors for maximum entropy models. In Proc. HLT-NAACL 2004, pages 305-311.
    • (2004) Proc. HLT-NAACL 2004 , pp. 305-311
    • Goodman, J.1
  • 14
    • 1642296635 scopus 로고    scopus 로고
    • Efficient support vector classifiers for named entity recognition
    • Hideki Isozaki and Hideto Kazawa. 2002. Efficient support vector classifiers for named entity recognition. In Proc. COLING 2002, pages 1-7.
    • (2002) Proc. COLING 2002 , pp. 1-7
    • Isozaki, H.1    Kazawa, H.2
  • 15
    • 80053419542 scopus 로고    scopus 로고
    • Japanese dependency parsing using a tournament model
    • Masakazu Iwatate, Masayuki Asahara, and Yuji Matsumoto. 2008. Japanese dependency parsing using a tournament model. In Proc. COLING 2008, pages 361-368.
    • (2008) Proc. COLING 2008 , pp. 361-368
    • Iwatate, M.1    Asahara, M.2    Matsumoto, Y.3
  • 16
    • 0024770899 scopus 로고
    • Space-efficient static trees and graphs
    • Guy Jacobson. 1989. Space-efficient static trees and graphs. In Proc. FOCS 1989, pages 549-554.
    • (1989) Proc. FOCS 1989 , pp. 549-554
    • Jacobson, G.1
  • 18
    • 9444232930 scopus 로고    scopus 로고
    • Evaluation and extension of maximum entropy models with inequality constraints
    • Jun'ichi Kazama and Jun'ichi Tsujii. 2003. Evaluation and extension of maximum entropy models with inequality constraints. In Proc. EMNLP 2003, pages 137-144.
    • (2003) Proc. EMNLP 2003 , pp. 137-144
    • Jun'ichi, K.1    Jun'ichi, T.2
  • 19
    • 24044538260 scopus 로고    scopus 로고
    • Maximum entropy models with inequality constraints: A case study on text categorization
    • Jun'ichi Kazama and Jun'ichi Tsujii. 2005. Maximum entropy models with inequality constraints: A case study on text categorization. Machine Learning, 60(1-3):159-194.
    • (2005) Machine Learning , vol.60 , Issue.1-3 , pp. 159-194
    • Jun'ichi, K.1    Jun'ichi, T.2
  • 20
    • 80053551637 scopus 로고    scopus 로고
    • Simple semi-supervised dependency parsing
    • Terry Koo, Xavier Carreras, and Michael Collins. 2008. Simple semi-supervised dependency parsing. In Proc. ACL 2008, pages 595-603.
    • (2008) Proc. ACL 2008 , pp. 595-603
    • Koo, T.1    Carreras, X.2    Collins, M.3
  • 21
    • 1642295001 scopus 로고    scopus 로고
    • Japanese dependency analysis using cascaded chunking
    • Taku Kudo and Yuji Matsumoto. 2002. Japanese dependency analysis using cascaded chunking. In Proc. CoNLL 2002, pages 1-7.
    • (2002) Proc. CoNLL 2002 , pp. 1-7
    • Kudo, T.1    Matsumoto, Y.2
  • 22
    • 85147247683 scopus 로고    scopus 로고
    • Fast methods for kernel-based text analysis
    • Taku Kudo and Yuji Matsumoto. 2003. Fast methods for kernel-based text analysis. In Proc. ACL 2003, pages 24-31.
    • (2003) Proc. ACL 2003 , pp. 24-31
    • Kudo, T.1    Matsumoto, Y.2
  • 23
    • 35548960691 scopus 로고    scopus 로고
    • Building a Japanese parsed corpus
    • Anne Abeillé, editor, Kluwer Academic Publishers
    • Sadao Kurohashi and Makoto Nagao. 2003. Building a Japanese parsed corpus. In Anne Abeillé, editor, Treebank: Building and Using Parsed Corpora, pages 249-260. Kluwer Academic Publishers.
    • (2003) Treebank: Building and Using Parsed Corpora , pp. 249-260
    • Kurohashi, S.1    Nagao, M.2
  • 24
    • 0142192295 scopus 로고    scopus 로고
    • Conditional random fields: Probabilistic models for segmenting and labeling sequence data
    • John D. Lafferty, Andrew McCallum, and Fernando C. N. Pereira. 2001. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proc. ICML 2001, pages 282-289.
    • (2001) Proc. ICML 2001 , pp. 282-289
    • Lafferty, J.D.1    McCallum, A.2    Pereira, F.C.N.3
  • 25
    • 80053342404 scopus 로고    scopus 로고
    • Experimental evaluation of LTAG-based features for semantic role labeling
    • Yudong Liu and Anoop Sarkar. 2007. Experimental evaluation of LTAG-based features for semantic role labeling. In Proc. EMNLP 2007, pages 590-599.
    • (2007) Proc. EMNLP 2007 , pp. 590-599
    • Liu, Y.1    Sarkar, A.2
  • 27
    • 9444233081 scopus 로고    scopus 로고
    • Maximum entropy estimation for feature forests
    • Yusuke Miyao and Jun'ichi Tsujii. 2002. Maximum entropy estimation for feature forests. In Proc. HLT 2002, pages 292-297.
    • (2002) Proc. HLT 2002 , pp. 292-297
    • Miyao, Y.1    Jun'ichi, T.2
  • 28
    • 80053394083 scopus 로고    scopus 로고
    • Exploring domain differences for the design of a pronoun resolution system for biomedical texts
    • Ngan L.T. Nguyen and Jin-Dong Kim. 2008. Exploring domain differences for the design of a pronoun resolution system for biomedical texts. In Proc. COLING 2008, pages 625-632.
    • (2008) Proc. COLING 2008 , pp. 625-632
    • Nguyen, N.L.T.1    Kim, J.-D.2
  • 29
    • 33746230843 scopus 로고    scopus 로고
    • An efficient algorithm for projective dependency parsing
    • Joakim Nivre. 2003. An efficient algorithm for projective dependency parsing. In Proc. IWPT 2003, pages 149-160.
    • (2003) Proc. IWPT 2003 , pp. 149-160
    • Nivre, J.1
  • 30
    • 84877666779 scopus 로고    scopus 로고
    • Learning combination features with L1 regularization
    • Short Papers
    • Daisuke Okanohara and Jun'ichi Tsujii. 2009. Learning combination features with L1 regularization. In Proc. HLT-NAACL 2009, Short Papers, pages 97-100.
    • (2009) Proc. HLT-NAACL 2009 , pp. 97-100
    • Okanohara, D.1    Jun'ichi, T.2
  • 31
    • 56449097022 scopus 로고    scopus 로고
    • The projectron: A bounded kernel-based perceptron
    • Francesco Orabona, Joseph Keshet, and Barbara Caputo. 2008. The projectron: a bounded kernel-based perceptron. In Proc. ICML 2008, pages 720-727.
    • (2008) Proc. ICML 2008 , pp. 720-727
    • Orabona, F.1    Keshet, J.2    Caputo, B.3
  • 32
    • 79960917591 scopus 로고    scopus 로고
    • Data catalysis: Facilitating largescale natural language data processing
    • Patrick Pantel. 2007. Data catalysis: Facilitating largescale natural language data processing. In Proc. ISUC, pages 201-204.
    • (2007) Proc. ISUC , pp. 201-204
    • Pantel, P.1
  • 34
    • 85119098424 scopus 로고    scopus 로고
    • Linear-time dependency analysis for Japanese
    • Manabu Sassano. 2004. Linear-time dependency analysis for Japanese. In Proc. COLING 2004, pages 8-14.
    • (2004) Proc. COLING 2004 , pp. 8-14
    • Sassano, M.1
  • 35
    • 84891610348 scopus 로고    scopus 로고
    • Semi-supervised training for the averaged perceptron POS tagger
    • Drahomíra "Johanka" Spoustová, Jan Hajič, Jan Raab, and Miroslav Spousta. 2009. Semi-supervised training for the averaged perceptron POS tagger. In Proc. EACL 2009, pages 763-771.
    • (2009) Proc. EACL 2009 , pp. 763-771
    • Spoustová, D.1    Hajič, J.2    Raab, J.3    Spousta, M.4
  • 36
    • 14344253846 scopus 로고    scopus 로고
    • Dynamic conditional random fields: Factorized probabilistic models for labeling and segmenting sequence data
    • Charles Sutton, Khashayar Rohanimanesh, and Andrew McCallum. 2004. Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data. In Proc. ICML 2004, pages 783-790.
    • (2004) Proc. ICML 2004 , pp. 783-790
    • Sutton, C.1    Rohanimanesh, K.2    McCallum, A.3
  • 38
    • 80053414342 scopus 로고    scopus 로고
    • An approximate approach for training polynomial kernel SVMs in linear time
    • Yu-Chieh Wu, Jie-Chi Yang, and Yue-Shi Lee. 2007. An approximate approach for training polynomial kernel SVMs in linear time. In Proc. ACL 2007
    • (2007) Proc. ACL 2007
    • Wu, Y.-C.1    Yang, J.-C.2    Lee, Y.-S.3


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